Sectors Performance
Sector Price Performance Distribution
For Date: 2026-10-02
Performance Heatmap (%)
| Sector | 1 Day | 1 Week | 1 Month | 3 Months | 6 Months | YTD | 1 Year |
| Consumer Discretionary | 1.13 | 0.95 | -4.20 | -6.05 | 1.95 | -6.65 | -7.51 |
| Technology | 1.01 | 2.71 | 8.83 | 10.64 | 47.10 | 38.81 | 40.20 |
| Industrials | 0.78 | 0.69 | -1.64 | -7.59 | 4.03 | 8.14 | 11.17 |
| Materials | 0.66 | -1.23 | -7.72 | -6.06 | -2.71 | 6.80 | 10.37 |
| Utilities | 0.38 | 1.48 | -6.66 | -12.96 | -13.51 | -6.52 | -7.46 |
| Communication Services | 0.35 | -0.77 | -1.87 | 0.66 | -0.98 | -5.08 | -4.41 |
| Real Estate | 0.32 | -1.31 | -6.68 | -8.66 | -1.07 | 2.64 | -0.02 |
| Consumer Staples | 0.25 | -2.13 | -5.85 | -5.25 | -0.98 | 4.95 | 5.46 |
| Energy | 0.19 | 1.16 | -3.50 | 18.04 | 6.78 | 39.51 | 45.21 |
| Financials | 0.06 | -1.29 | -7.23 | -3.83 | 8.39 | -1.78 | 1.48 |
| Health Care | -0.01 | -2.97 | -3.91 | 1.49 | 13.70 | 7.78 | 17.54 |
Ask the market a question. Get a calculated answer.
The AI is not a chatbot bolted onto a document store. It calls the same analytics engine that powers every screen on this platform — so what comes back is a number it computed from raw history, with the command that produced it.
86,000+ instruments
Global equities, ETFs, funds, options, FX, commodities, crypto, economics, filings, transcripts and news — one normalised symbol universe with adjusted history.
A real analytics engine
Screening, backtesting, technicals, options analytics, correlations, seasonality and factor models — computed on demand from raw prices, never a stale cache.
It shows its working
Answers arrive with the charts, tables and tool calls behind them, so you can check the number instead of trusting a paraphrase.
Your own documents
Upload filings, decks and research. Ask across them and the answer cites the page it came from.
Agents and workflows
Multi-step research that runs the platform's tools for you — screen, pull the history, compute, compare, then write it up.
MCP, CLI and API
The same command catalogue from Claude, your own agent, a shell or your pipeline. The answer on screen is the answer your job gets at 4am.
You ask
“How does NVDA usually trade through earnings?”
It calls
→ ka.options_expected_move(NVDA)
It answers
NVDA has averaged a 9.2% absolute move on the day after earnings and closed higher 67% of the time. Two in three reactions land between −4.2% and +16.3% — the distribution is skewed right, not symmetric.
Every figure computed live from our own history — not scraped, not summarised.
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